Evidence map›Paper›PMID 32538517›Full record

ArticleEuropean journal of pain (London, England)2020

Disentangling trait versus state characteristics of the Pain Catastrophizing Scale and the PHQ-8 Depression Scale.

Levent Dumenci, Kurt Kroenke, Francis J Keefe, Dennis C Ang, James Slover, Robert A Perera, Daniel L Riddle

Open access · greenAbstract read
In one paragraph

Article in European journal of pain (London, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 21% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Pooled it
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  6. Observational
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 6 institutions in 1 country.

Levent DumenciDepartment of Epidemiology and Biostatistics, Temple University, Philadelphia, PA, USA.
Kurt KroenkeIndiana University School of Medicine, and Regenstrief Institute, Indianapolis, IN, USA.
Francis J KeefePain Prevention and Treatment Research, Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA.
Dennis C AngSection of Rheumatology, Department of Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA.
James SloverDepartment of Orthopaedic Surgery, New York University Medical Center, New York, NY, USA.
Robert A PereraDepartment of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA.
Daniel L RiddleDepartments of Physical Therapy, Orthopaedic Surgery and Rheumatology, Virginia Commonwealth University, Richmond, VA, USA.
Virginia Commonwealth University · USColumbia University Irving Medical Center · USDuke University · USRegenstrief Institute · USTemple University · USWake Forest University · US

Funding

Center for Clinical and Translational ResearchUL1TR000058 · NCATS · VIRGINIA COMMONWEALTH UNIVERSITY · PI MOELLER, FREDERICK GERARD · 2012 to 2015
$12.5M
Knee Arthroplasity Pain Coping Training (KAST Pain): A Randomized TrialUM1AR062800 · NIAMS · VIRGINIA COMMONWEALTH UNIVERSITY · PI RIDDLE, DANIEL L · 2012 to 2016
$5.2M
NCATS NIH HHS UL1 TR000058NIAMS NIH HHS UM1 AR062800
6 · The paper itself

Abstract

backgroundResearch on the role of trait versus state characteristics of a variety of measures among persons experiencing pain has been a focus for the past few decades. Studying the trait versus state nature of the Pain Catastrophizing Scale (PCS) and the Patient Health Questionnaire (PHQ-8) depression scale would be highly informative given both are commonly measured in pain populations and neither scale has been studied for trait/state contributions.

methodsThe PHQ-8 and PCS were obtained on persons undergoing knee arthroplasty at baseline, 2-, 6- and 12-month post-surgery (N = 402). The multi-trait generalization of the latent trait-state model was used to partition trait and state variability in PCS and PHQ-8 item responses simultaneously. A set of variables were used to predict trait catastrophizing and trait depression.

resultsFor total scores, the latent traits and latent states explain 63.2% (trait = 43.2%; state = 20.0%) and 50.2% (trait = 29.4%; state = 20.8%) of the variability in PCS and PHQ-8, respectively. Patients with a high number of bodily pain sites, high levels of anxiety, young patients and African-American patients had high levels of trait catastrophizing and trait depression. The PCS and the PHQ-8 consist of both enduring trait and dynamic state characteristics, with trait characteristics dominating for both measures.

conclusionClinicians and researchers using these scales should not assume the obtained measurements solely reflect either trait- or state-based characteristics. SIGNIFICANCE: Clinicians and researchers using the PCS or PHQ-8 scales are measuring both state and trait characteristics and not just trait- or state-based characteristics.

Indexed as

CatastrophizationDepressionHumansPain MeasurementPatient Health QuestionnaireProspective Studies

Identifiers

PMID32538517
PMCPMC7686072
OpenAlexW3034292381

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.